Ramesh Suragam

Data Scientist

Wipro Technologies•  September 2018 - August 2019

• Evaluate Customer Life Time Value, predicted Customer Churn Rate, and built customer recommendation systems for existing customers. • Predict sentiments of email feedback from customers to determine positivity using Deep Learning models and NLP techniques of stemming, lemmatization using Python libraries. • Lead initiatives for customer based analytics such as attribution modelling, customer journey, messaging optimization, personalization, CLV. Implement Hidden Markov model to identify future customer interaction with multichannel touchpoint. • Work with credit card Profit and risk analysis team to analyse the current customer base to model better offers and schemes to maximize the profits. • Develop statistical models and applied them to assign a risk score to credit applications and existing credit accounts. Improve the models and monitor the effect of score based decisions. • Build revenue models using linear regression, regression trees, polynomial regression, GBM, SVR and NN.

Data Scientist

CGI•  May 2016 - August 2018

• Identified customers and modelled potential savings (~$500K in two months) associated with a recommended switch of selected clients to a different processor prior to the fiscal year's peak processing month. • Design and built real-time contextual behavioural personalization system using econometric and machine learning to predict customer's behaviour, and help them to navigate through products of their choice. Low latency models learn and predict online, enabling it to respond constantly to changes in card member's payment behaviour at various stages, with accuracy over 90%. • Devise a Customer-Centric Pricing model for discounts using collaborative filtering, low-rank matrix factorization, leading to an increase in revenue by 3%. • Used Statistical methods to analyse the performance of each consumer stores across 12 provinces on 30 studies. • Implemented forecasting algorithms that efficiently detect seasonality trends and thereby enhance sales/demand prediction accuracy by 20%. • Enhanced statistical models(linear mixed models) and developed A/B testing to predict the best products for commercialization that effectively facilitated business planning and sales & operations. • Work closely with business team and engineering team to define the scope of problem and development plan. • Formulated credit risk scorecards and marketing response models using SQL to evangelize the complex technical analysis into easily digestible reports for top bank executives.

Programmer Analyst(Data Engineer)

CGI•  July 2013 - May 2016

• Develop ETL(informatica) workflows by integrating different data sources, performance tuning of ETL and SQL codes, and recurring issues automation. • Assist senior data engineers and data scientists in building data pipelines, feature engineering, model training frameworks and model deployments at scale. • Understand data issues in the data warehouse, analyse them and resolve. • Assist in performing statistical analysis develop ad-hoc reports using tableau. • Performance tuning and generate automation scripts in ETL, SQL, python and Unix .

National University of Ireland, Maynooth

Data Science, MS•  September 2019 - September 2020

Master of Science in Data Science; Result: 1.1 First Class Honours